6506 results about "Digital signal" patented technology

The invention discloses a DC-DC power supply dynamic response optimization system based on digital PID, which relates to the technical field of DC-DC power supply dynamic response optimization, and comprises a voltage and current sampling module, a reference signal generation module, an output signal generation module, a digital signal generation module, a control module and an output signal generation module, the digital PID controller calculates control output according to errors, the PWM signal generation module generates corresponding PWM signals according to the control output, the power switch driving module amplifies the signals to drive a switch tube, the load monitoring module monitors load changes in real time, output of the load monitoring module can be fed back to other modules, and power supply dynamic response optimization is achieved. According to the invention, the dynamic response performance of the DC-DC power supply is remarkably improved, the output fluctuation is reduced, the recovery time is shortened, the power supply efficiency is improved, the stability is guaranteed by adopting multiple anti-interference design, peripheral elements are reduced, miniaturization is realized, the cost is reduced, fault diagnosis is realized, and the service life is prolonged.

The invention discloses a 5G base station power supply state intelligent monitoring system and method, and belongs to the technical field of intelligent monitoring. According to the system, operation parameters of a 5G base station power supply are acquired in real time through the data acquisition module, and after the operation parameters are processed by the signal conditioning and conversion module, the master control processing unit analyzes digital signals in real time, detects abnormal states and generates alarm information. The communication module is responsible for data transmission and instruction receiving, and the power management and safety protection module provides overvoltage, undervoltage, overcurrent and short circuit protection and triggers emergency measures. The artificial intelligence analysis module performs fault prediction and performance optimization based on historical data and real-time data, and the remote monitoring terminal realizes data visual monitoring and management. According to the invention, the real-time performance and accuracy of monitoring are improved, unified management of multiple base stations is realized, the operation and maintenance cost is reduced, and stable operation of a 5G communication network is guaranteed.

The invention discloses a transcranial electrical stimulation intracranial vector electric field detection device and method, and belongs to the transcranial electrical stimulation intracranial electric field detection technology, the device inputs an individual head model in a stimulation system, sets a target spot and calculates transcranial electrical stimulation parameters; the implantation position and angle of the vector detection electrode are planned through the navigation system, electrical stimulation is applied to a brain target area through the stimulation electrode, and intracranial electric signals are collected in real time through the vector detection electrode; performing high-precision amplification on the acquired weak signal, and converting the weak signal into a digital signal; the collected electric field signals are calculated and processed in real time, and electric field distribution generated by transcranial electrical stimulation in the brain is analyzed and visualized; according to the method, time domain and frequency domain analysis is carried out on electric signals before and after stimulation, the influence of stimulation on neural signals in a detection area is evaluated, and high-precision measurement of the intensity and direction of a three-dimensional electric field is achieved through the design of a high-precision and multi-layer vector detection electrode.

The invention belongs to the technical field of signal acquisition and processing, and discloses a low-noise biopotential signal acquisition system and a low-noise biopotential signal processing method. An original bioelectricity signal of a human body is collected through an electrode array, and analog-to-digital conversion is carried out after the signal is processed by a multi-stage self-adaptive filtering and amplifying circuit. A digital signal is sequentially subjected to adaptive wavelet transform denoising and empirical mode decomposition to obtain a multi-level intrinsic mode function set, an intrinsic mode function of a characteristic frequency band is extracted from the multi-level intrinsic mode function set, and the signal is reconstructed. Introducing a dual noise reduction mechanism combining adaptive wavelet transform and empirical mode decomposition; a signal quality real-time evaluation system is established, and system parameters including the gain of a variable gain amplifier and the bandwidth of a dynamic band-pass filter are dynamically adjusted through closed-loop feedback. The self-adaptive optimization of the whole biopotential signal acquisition process is realized, various interferences are effectively inhibited, the signal characteristics are reserved, and the signal-to-noise ratio is remarkably improved.

The invention discloses a multichannel electrophysiological signal acquisition system and an acquisition method thereof, and the multichannel electrophysiological signal acquisition system comprises a power supply module electrically connected with a controller, an analog front-end chipset, a filter module and an analog-to-digital conversion module; the analog front-end chip set is used for acquiring an analog signal and preprocessing the analog signal; the pre-processed analog signal is converted into a digital signal through a filter module and an analog-to-digital conversion module, and the digital signal is transmitted to a controller; the filter module is used for filtering and denoising; the timer module connected with the controller generates a sampling frequency, transmits the sampling frequency to the analog-to-digital conversion module, and provides a time sequence signal for the analog-to-digital conversion module. The invention discloses a multi-channel electrophysiological signal acquisition system, which solves the problem of synchronous sampling time sequence control of a high-density electrode array and eliminates signal phase deviation caused by clock jitter among multiple channels under the constraint of maintaining the total power consumption of the system. And real-time power frequency interference suppression is realized.

The invention discloses a particle size measuring device based on combination of a dynamic light scattering method and a sedimentation method and a measuring method thereof. The particle size measuring device comprises a laser, a light intensity adjusting unit, a sample pool, a thermostatic bath, a PD detector, an optical fiber head, an APD detector, a data acquisition unit, a PC and a control unit. The laser emits incident laser, the incident laser passes through the light intensity adjusting unit, penetrates through the sample cell and a sample and then enters the PD detector, and a transmission light signal is collected through the data acquisition unit and transmitted to software for calculating the particle size and concentration of settled large particles; scattered light is received by an optical fiber head with a fixed angle of 90 degrees or 160-175 degrees and is converted into a digital signal by an APD detector, and the digital signal enters a data acquisition unit and is transmitted to software for calculating the particle size of particles in a non-settling nanometer range. According to the technical scheme provided by the invention, the particle size distribution information of the wide-distribution particle dispersion system in a nano-micron range can be measured in a testing process.

The invention relates to a digital lock-in amplifier based on a frequency adaptive technology and a weak signal acquisition system and method, and the system comprises a front-end signal processing module which is used for obtaining a weak signal to be detected; the frequency self-adaptive tracking module is used for performing fast Fourier transform on the frequency of the weak signal to be measured to obtain the position of the maximum spectral line so as to synthesize a frequency control word, further generate a local reference signal and simultaneously adjust the coefficients of a low-pass filter and a loop filter and the series adjustment mode of a carrier synchronization ring; the multi-rate narrow-band low-pass filter module is used for multiplying the digital signal by a local reference signal and then carrying out filtering and down-sampling on a high-frequency signal to obtain a plurality of mutually orthogonal difference frequency components; the vector operation module is used for carrying out vector operation on the plurality of mutually orthogonal difference frequency components to obtain the phase and the amplitude in the weak signal to be measured; and the man-machine interaction module is used for displaying and storing the phase and the amplitude in the weak signal to be detected.

The invention discloses a dynamic neutral position and boundary self-calibration method and system of a joystick, and belongs to the technical field of engineering machinery and mining equipment control, and the method comprises the following steps: S1, electrifying equipment, and selecting a mode; s2, calibrating a dead zone; s3, setting a threshold value; s4, data storage; and S5, exiting and applying. According to the dynamic median and boundary self-calibration method and system of the joystick, when the joystick works, a physical manipulated variable is converted into an original electric signal through a joystick sensing unit, then the original electric signal is received through a signal processing module and subjected to signal conditioning, and an analog signal is converted into a digital signal which can be processed by a microprocessor; all logical judgments are executed through the main control unit, a user issues an instruction through a user configuration interface and directly inputs the instruction to the main control unit, the main control unit and the nonvolatile memory carry out bidirectional data interaction to realize permanent storage and calling of dead zone parameters, and the main control unit generates a final control instruction to be output after processing all information. And the actuating mechanism is driven.

A method for monitoring a rock burst in ultra-thin coal seams, which method belongs to the technical field of fully mechanized coal mining in ultra-thin coal seams. The method comprises: respectively recording the acquired propagation times and propagation velocities of attenuated seismic waves from artificial seismic sources and the acquired propagation time and propagation velocity of a rock burst, and comparing different seismic wave signals and real-time rock burst signals passing through a mining area; converting the different seismic wave signals and the real-time rock burst signals into digital signals, and determining via comparison whether the digital signals have waveforms during the rock burst; when the digital signals have waveforms during the rock burst, identifying the waveforms of micro-seismic events, and determining the energy intensity of the rock burst; locating rock burst sources, and obtaining an intersection area of the rock burst sources, so as to obtain a seismic source position after a delineated range is reduced; and on the basis of acquired real-time pressure data in underground rock or coal seams, obtaining the positions of the maximum pressure and maximum pressure changes of a seismic source, and the numerical values thereof by means of analyzing a real-time pressure value and a real-time strain change rate. By means of the method, potential hazardous areas can be monitored. The present invention further relates to a system for monitoring a rock burst in ultra-thin coal seams.

The invention discloses an accurate zero crossing point control method for a built-in relay of a large-current electric energy meter, which relates to the technical field of power electronics and intelligent metering and comprises the following steps of: receiving a power grid voltage digital signal, determining a voltage zero crossing point by comparing symbol changes of adjacent sampling values, establishing a phase corresponding relation between voltage and current, and calculating a current phase corresponding relation; generating current zero crossing point prediction data; when a relay switching instruction is received, the specific moment of the next current zero crossing point is calculated, and the control signal sending moment is determined; a relay driving control signal is sent, the actual action completion moment of the relay is collected, the deviation from the expected zero crossing moment is calculated, and the mechanical action delay time parameter of the relay is corrected. By predicting the current zero-crossing time and considering the mechanical action delay characteristic of the relay, accurate switching of the built-in relay at the actual current zero-crossing point is achieved, meanwhile, the self-adaptive adjusting capacity is achieved, the arc energy during large-current switching is reduced, the service life of the relay is prolonged, and the reliability of the electric energy meter is improved.

The invention provides an underwater ultrasonic Doppler real-time analysis method and device based on a digital transducer, and relates to the technical field of data analys.The method comprises the steps that 1, multiple beams of directional ultrasonic waves are emitted into drilling fluid through a digital transducer array on the outer wall of a marine riser, echo signals reflected by gas-liquid two-phase flow are received, and the digital transducer array is used for receiving the echo signals; performing real-time digital conversion on the echo signal to generate an original digital signal containing phase and amplitude information; 2, Doppler frequency shift feature extraction is conducted on the original digital signals, and the real-time movement speed and direction of bubbles in the drilling fluid are determined by calculating the frequency deviation of reflected ultrasonic waves and transmitted ultrasonic waves. Through the digital transducer array and the ultrasonic Doppler technology, accurate measurement of motion parameters of bubbles in drilling fluid, real-time calculation of local gas content and early warning and grading response of gas cut are achieved, and the safety and the intelligent level of drilling operation are improved.

The invention discloses an intelligent underwater sound signal processing system and method based on multi-sensor data fusion, and belongs to the field of underwater signal processing. A plurality of sensors are used for collecting underwater sound signals, linear acceleration, angular velocity and other information of an underwater target and outputting continuous analog signals; then the differential signals are transmitted to a signal conditioning module, gain is dynamically adjusted according to target intensity, amplified differential signals are output to an analog-to-digital conversion module, high-precision digitalization is carried out through a 24-bit delta-sigma ADC, digital signals are output to a main control unit, and the main control unit carries out multi-sensor data fusion and target orientation calculation; and finally, the main control unit uploads the underwater acoustic signal and the equipment attitude information data to an upper computer through an RS485 bus for man-machine interaction. The scheme is based on multi-sensor data fusion, can realize high-precision target detection and positioning in a dynamic underwater environment, and has wide popularization and application values.

The invention discloses a noise reduction method and system for a high-performance TWS Bluetooth audio chip, and relates to the technical field of acoustoelectric integration, and the method comprises the steps: collecting an environment noise signal, synchronously obtaining a Bluetooth radio frequency interference signal, converting the Bluetooth radio frequency interference signal into a digital signal through a 24-bit analog-to-digital converter, and outputting a multi-modal noise feature matrix; performing noise separation and reverse sound wave generation on the multi-modal noise characteristic matrix by using a pre-trained lightweight CycleGAN model, and outputting a reverse sound wave signal; monitoring auditory meatus tightness parameters in real time, dynamically adjusting phase offset and frequency response balance parameters of the mixed noise reduction signals, and outputting optimized noise reduction signals adaptive to the current wearing state; and performing parameter calibration on the optimized noise reduction signal through anechoic chamber scene simulation and laser interferometer phase detection to generate a noise reduction control instruction set. According to the invention, the noise interference problem of the TWS earphone in a complex environment is effectively solved.

The invention discloses an intelligent identification system and method based on time-frequency feature fusion and adaptive classification, and relates to the technical field of power equipment state monitoring. Comprising an ultrahigh frequency signal processing unit, a filter amplification unit, an analog-to-digital conversion unit, a digital signal preprocessing unit, a multi-dimensional feature extraction unit, a discharge phase analysis unit, a classification model optimization unit, an interference elimination unit, a defect type identification and diagnosis unit and a discharge source positioning unit. The ultrahigh frequency signal processing unit is used for collecting and transmitting partial discharge weak electromagnetic signals, and the filtering and amplifying unit is used for filtering, eliminating interference and amplifying signal amplitude. Through the ultrahigh frequency signal processing unit, the filtering and amplifying unit and the analog-to-digital conversion unit, weak electromagnetic signals are accurately collected, interference is efficiently filtered out, the signals are amplified and converted, the accuracy and effectiveness of the detection process are improved, and the misjudgment risk is reduced through pulse segmentation and normalization, multi-dimensional feature extraction and classification model establishment and optimization.

The invention relates to the technical field of advertisement shooting, in particular to a holder self-adaptive tracking control method based on visual identification, which comprises the following steps of: acquiring a scene image digital signal in real time through a camera, then extracting the coordinate, the size and the motion trail of a detection target, and adopting an optical flow motion estimation algorithm in the extraction process, the optical flow motion estimation algorithm can calculate the motion information of the target by analyzing the motion of the pixel points in the image, and is combined with pure extraction of static information such as coordinates and sizes, so that the state of the detected target can be described more comprehensively and dynamically, the location of the target can be known, and the motion of the target can be accurately mastered; and then, according to the motion trail of the detection target, calculating and establishing a mapping relation between a pan-tilt angle and a camera visual field, and calculating the angle of the pan-tilt needing to be adjusted when the detection target shoots the advertisement and the detection target moves through the mapping relation between the pan-tilt angle and the camera visual field, so that the detection target can be always located at the central point coordinate of the image digital signal.

An optical ranging system includes a coherent IQ receiver configured to receive a radio frequency (RF)-encoded optical signal, generate an in-phase (I) electrical signal and a quadrature (Q) electrical signal based on the RF-encoded optical signal; a first analog-to-digital converter (ADC) configured to convert the I electrical signal into an I digital signal; a second ADC configured to convert the Q electrical signal into a Q digital; and a processing circuit configured to generate a power signal having the target frequency by squaring the I digital signal and the Q digital signal, and summing a squared I digital signal and a squared Q digital signal. The processing circuit is configured to analyze the power signal to determine a signal phase corresponding to signal peaks associated with the target frequency, and determine a distance value based on a phase difference between the signal phase and a reference power signal.

The invention discloses an online EIS battery pack performance parameter estimation algorithm, and relates to the technical field of battery management, and the algorithm comprises the steps: generating a basic frequency conversion excitation signal through a digital signal generator, and loading the basic frequency conversion excitation signal to a working battery pack through a self-adaptive frequency sweeping strategy; acquiring a response signal, analyzing an impedance real part and an imaginary part of the battery pack at each frequency point through a digital orthogonal synchronous demodulation technology, and constructing an electrochemical impedance spectrum; extracting multi-dimensional health features from the electrochemical impedance spectrum, inputting the multi-dimensional health features into a fusion deep learning model, and estimating the state of charge and the state of health of the battery; and generating a system optimal control signal based on the estimated state of charge and state of health. According to the algorithm, portable, online and real-time detection of the performance parameters of the battery system in the working state is realized, and the application scene limitation of traditional EIS equipment is broken through; and through the optimized signal processing and intelligent algorithm, the detection stability and response speed are improved.

The invention relates to the technical field of particle accelerators, in particular to a transverse feedback system with a switchable excitation direction and a control method thereof, and the system comprises a beam position detector BPM which is used for measuring a beam signal; the RF front end is used for receiving the beam signal sent by the beam position detector BPM and carrying out amplification and filtering processing; the ADC module is used for converting the beam signal into a digital signal; the digital signal processing module is used for carrying out digital signal processing calculation to obtain an excitation signal; the DAC module is used for carrying out digital-to-analog conversion; the power divider is used for adjusting the phase of the excitation signal; the exciter comprises four Kickers with electrodes, a power amplifier, a low-pass filter and a matched load and is used for applying a transverse excitation signal to the beam current, and the problems that in the prior art, a transverse feedback system Kicker occupies a large longitudinal space, the system is complex, and precision and efficiency are low are solved.

The invention discloses a multi-channel analog-to-digital converter for multi-channel frequency division multiplexing and a conversion circuit and method thereof, and the frequency division multiplexing multi-channel analog-to-digital conversion circuit comprises an analog frequency conversion module which is used for receiving N paths of modulation clock signals, and generating N paths of modulation clock signals according to the modulation clock signals, n paths of input signals are modulated to preset frequencies of the input signals respectively, and N paths of modulation signals are obtained; wherein N is greater than or equal to 2, and N is a positive integer; the frequency bands where the N paths of modulation signals are located are not overlapped; the analog adder is used for combining the N paths of modulation signals to obtain one path of analog signal; the input end of the analog-digital conversion module is connected with the analog-digital conversion module; the digital logic control module is used for receiving the N paths of modulation clock signals and separating the digital signals into N paths of digital signals which are output in parallel. Multi-channel analog-to-digital conversion can be realized by adopting one analog-to-digital converter, the hardware volume, cost and power consumption can be reduced, and the analog-to-digital conversion rate and precision can be improved.

The invention discloses a noise signal recognition method based on deep learning. The method comprises the steps of original signal collection, signal preprocessing, noise recognition feature extraction, noise signal recognition model establishment and noise signal intelligent recognition. The invention relates to the technical field of digital signal data processing, in particular to a noise signal identification method based on deep learning, and innovatively provides a self-adaptive signal mode decomposition method based on a combined judgment mechanism of energy threshold value judgment and energy range value judgment. Decoupling and reservation of different frequency bandwidth information in an original signal can be effectively completed, and the recognition accuracy of non-stationary communication noise is improved; a frequency band filter bank constructed based on a Gaussian function is introduced, so that the accuracy of communication signal identification is improved; a method for constructing a noise recognition model by fusing graph neural network structure modeling and an original type reference vector matching mechanism is innovatively proposed, and the recognition robustness of the model to non-stationary communication interference signals is improved.

The present disclosure involves a medical device. The medical device includes an elongate cable assembly having a distal connector, a proximal connector, and a cable body coupling the proximal and distal connectors. The distal connector is configured for coupling with a diagnostic medical device. The proximal connector is configured for coupling with a medical measurement system. An electronic component is located inside the distal connector or the associated cable housing. The electronic component includes an analog-to-digital converter (ADC) and a microprocessor. The ADC is configured to receive medical data gathered by the diagnostic medical device and convert the medical data into digital signals. The microprocessor is coupled to an output of the ADC and configured to process the digital signals into a format that is readable by the medical measurement system.

The present application relates to a power distribution Internet of Things terminal debugging and testing system. The system comprises a cloud test service center (100), a power distribution Internet of Things terminal debugging device (200) and an intelligent gateway (300); the intelligent gateway (300) is used for acquiring terminal information of power distribution Internet of Things terminals and uploading the terminal information to the cloud test service center (100); the cloud test service center (100) is used for issuing a test command to the power distribution Internet of Things terminal debugging device (200) on the basis of the terminal information; the power distribution Internet of Things terminal debugging device (200) is used for carrying out signal conversion on the test command, determining an analog signal corresponding to the test command, and applying the analog signal to the power distribution Internet of Things terminals; the intelligent gateway (300) is used for acquiring digital signals and transmitting the digital signals to the cloud test service center (100), wherein the digital signals are obtained by converting the analog signal by the power distribution Internet of Things terminals; the cloud test service center (100) is used for determining test results of the power distribution Internet of Things terminals on the basis of the digital signals. Fully-automatic closed-loop debugging can be implemented, and the power distribution efficiency is greatly improved.

Systems and methods are disclosed comprising techniques for signal processing, such as receiving a first digital artifact comprising unstructured alphanumeric signal data indicating contextual information associated with a decision logic condition, identifying a set of non-compliant alphanumeric signals from the unstructured alphanumeric signal data, generating a set of masking elements comprising a mapping to the set of non-compliant alphanumeric signals, generating a second digital artifact comprising alphanumeric signal data that substitutes the identified non-compliant alphanumeric signals with the set of masking elements, determining a set of signal domain categories for the second digital artifact corresponding to alphanumeric signal properties satisfied by the alphanumeric signal data of the second digital artifact, generating a composite alphanumeric signal for the second digital artifact based on the determined set of signal domain categories, and generating for display at a user interface a set of guidance artifacts generated using the composite alphanumeric signal.

The present invention discloses a method and device for simultaneously measuring the bending vibration and torsional vibration of a rotating machinery shaft. The gear disk is installed on the shaft to be measured, and the gear disk is driven to rotate by the shaft to be measured. An alternating voltage signal is output by the eddy current sensor and converted into a digital signal by the software part, so as to obtain the original vibration signal. The maximum value finding method is used twice to extract the bending vibration and torsional vibration of the shaft. Through the above method, the simultaneous measurement of the torsional vibration and bending vibration of the shaft can be realized. The same set of sensors and instruments are used for the two types of vibration measurements, and the cost is relatively low.

A device (100) and method for self-calibrating a radiofrequency transmitter are disclosed, the device comprising: first circuitry (120) for receiving a reference phase value (ϕ) and configured to output a first analog signal (AI) based on the reference phase value (ϕ); second circuitry (130) for receiving said reference phase value (ϕ) and configured to output a second analog signal (AQ) based on the reference phase value (ϕ); an IQ modulator (110) coupled to receive an input signal (LO), said first analog signal and said second analog signal, and configured to provide an IQ modulator output signal (RFout) based on said input signal, said first analog signal (AI) and said second analog signal (AQ); and compensation control circuitry (150) coupled to receive the IQ modulator output signal (RFout) and configured, during calibration, to output at least one compensation signal indicative of a compensation value based on the IQ modulator output signal (RFout); wherein at least one of said first circuitry (120) and said second circuitry (130) comprises: a digital signal generating portion (210, 310) for generating a digital signal (DI, DQ) based on the reference phase value (ϕ) and at least one said compensation value, a sigma-delta modulator portion (220, 320) coupled to receive the digital signal (DI, DQ) and configured, during calibration, for sigma-delta modulating the digital signal (DI, DQ); and a digital-to-analog converter (230, 330), coupled, during calibration, to receive the modulated digital signal provided by the sigma-delta modulator portion (220, 330) and configured to output said respective first / second analog signal (AI, AQ).

In order to solve the problem that quick response and distortionless recording of ultrahigh-frequency partial discharge signals are difficult to realize when accidental pulses are generated in the prior art, the invention relates to a dual-channel parallel processing architecture for ultrahigh-frequency partial discharge signals, which comprises a signal cloning circuit and a signal processing circuit, the ultrahigh-frequency partial discharge module is used for receiving ultrahigh-frequency partial discharge signals and synchronously outputting the ultrahigh-frequency partial discharge signals as first target signals and second target signals after lossless copying; the low-gain channel circuit is used for performing buffer transmission for maintaining an original bandwidth and a dynamic range on the first target signal to generate a first gain signal; the high-gain channel circuit is used for performing gain amplification on the second target signal to generate a second gain signal; the digital signal processing unit is used for performing synchronous clock control on the low-gain channel circuit and the high-gain channel circuit; and the FPGA chip is integrated in the digital signal processing unit and is used for performing fusion splicing processing on the first gain signal and the second gain signal based on a waveform fusion splicing algorithm and generating a fusion signal.

The present invention discloses a pulse generator and a pulse rod, which relate to the field of pulse circuit technology. The pulse generator includes a frequency control unit, a dual closed-loop pulse amplification unit, a digital signal processing unit and an adaptive power management unit. The frequency control unit includes an environmental sensor and a microcontroller. The microcontroller can calculate a preset pulse frequency based on information transmitted by the environmental sensor. The input end of the dual closed-loop pulse amplification unit can receive a pulse signal transmitted by the microcontroller, amplify it to a preset pulse frequency, and provide a pulse current to an electrostatic elimination needle. The digital signal processing unit can digitize the pulse signal to enhance the anti-interference ability of the pulse signal. The adaptive power management unit includes a dynamic voltage regulation module electrically connected to an external power supply, and the dynamic voltage regulation module can dynamically adjust the output voltage. The technical solution provided by the present invention can provide a pulse generator with high stability, a wide adjustment range and strong anti-interference ability.

Techniques are described for embedded device based fingerprint signing and public ledger registering management. A digital fingerprint associated with media content can be identified. An embedded integrated circuit (IC) of the computing device can be utilized to store security data associated with the media content. The security data can include at least one digital certificate. The at least one digital certificate can include a device certificate utilized to generate a cryptographic signature associated with the metadata and the digital fingerprint. A file can be generated and registered with a public ledger. The file can include the digital fingerprint, the metadata, the at least one certificate, and the cryptographic signature.

The present application relates to a waveform file conversion method and apparatus for chip testing, and a computer readable storage medium. The method comprises: performing content analysis on a waveform file to be converted, to acquire period information, pin information, and state information of pins in each period of said waveform file; generating a PAT-format digital signal waveform file; and on the basis of a mapping relationship between pins and ATE channels, converting the PAT-format digital signal waveform file into a binary vector file for ATE testing. A waveform file in any format is converted into a PAT-format digital signal waveform file which uses periods as rows and pins as columns, so that each row vector not only contains current time information but also contains a logical state of each pin; in addition, to facilitate understanding, the PAT-format digital signal waveform file is further converted into a binary vector for ATE testing, so that efficient processing of waveform files in a plurality of different formats can be realized, thereby improving the universality of conversion.

The invention discloses an IO pin multiplexing circuit, a control method, a chip and electronic equipment, and the circuit comprises a gating module which is connected with a chip core and is used for transmitting a first enabling signal and / or a second enabling signal according to an on-chip control signal; the control word coding module is respectively connected with the gating module and the off-chip, and is used for enabling an IO pin to work in a control word coding mode according to the first enable signal; the digital signal input module is respectively connected with the gating module and is used for enabling an IO pin to work in a digital signal input mode according to a second enable signal; and the ESD module is connected with the digital signal input module and the control word coding module and is used for providing electrostatic protection. According to the invention, a pin function multiplexing technology is adopted, a control word writing function can be realized when the chip is just started through an enable signal switching function, a digital signal transmission function can be realized when the chip normally runs, the hardware cost is reduced, and the consumption of pin resources is reduced.